In many real-world applications such as marketing [1]}, healthcare [2]}, [3]}, [4]}, [5]}, [6]} and education [7]}, it is common to reason about the effects of deploying one policy, based on data collected from a different policy. For instance, in healthcare, given the treatment history of a patient in ICU, we might be concerned about whether patient outcomes would improve if we changed the treatment protocol. Such problems have been posed as off-policy evaluation (OPE) tasks in reinforcement learning, and several methods have been proposed for performing OPE estimation.
